






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


snake_case__   :						Optional[Any]													=   {
    """configuration_tapas""": ["""TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TapasConfig"""],
    """tokenization_tapas""": ["""TapasTokenizer"""],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__   :						Tuple													=   [
     """TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """TapasForMaskedLM""",
     """TapasForQuestionAnswering""",
     """TapasForSequenceClassification""",
     """TapasModel""",
     """TapasPreTrainedModel""",
     """load_tf_weights_in_tapas""",
 ]
try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__   :						Optional[Any]													=   [
     """TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """TFTapasForMaskedLM""",
     """TFTapasForQuestionAnswering""",
     """TFTapasForSequenceClassification""",
     """TFTapasModel""",
     """TFTapasPreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
 from .tokenization_tapas import TapasTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tapas import (
      TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
      TapasForMaskedLM,
      TapasForQuestionAnswering,
      TapasForSequenceClassification,
      TapasModel,
      TapasPreTrainedModel,
      load_tf_weights_in_tapas,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_tapas import (
      TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFTapasForMaskedLM,
      TFTapasForQuestionAnswering,
      TFTapasForSequenceClassification,
      TFTapasModel,
      TFTapasPreTrainedModel,
  )


else:
 import sys

 snake_case__   :						List[str]													=   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowercase    :   Optional[int]						=			{
    'configuration_mobilevit': ['MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MobileViTConfig', 'MobileViTOnnxConfig'],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase    :   List[str]						=			['MobileViTFeatureExtractor']
		lowercase    :   Tuple						=			['MobileViTImageProcessor']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase    :   List[Any]						=			[
		    'MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'MobileViTForImageClassification',
		    'MobileViTForSemanticSegmentation',
		    'MobileViTModel',
		    'MobileViTPreTrainedModel',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase    :   List[Any]						=			[
		    'TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TFMobileViTForImageClassification',
		    'TFMobileViTForSemanticSegmentation',
		    'TFMobileViTModel',
		    'TFMobileViTPreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig, MobileViTOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_mobilevit import MobileViTFeatureExtractor
				from .image_processing_mobilevit import MobileViTImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mobilevit import (
				    MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MobileViTForImageClassification,
				    MobileViTForSemanticSegmentation,
				    MobileViTModel,
				    MobileViTPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_mobilevit import (
				    TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFMobileViTForImageClassification,
				    TFMobileViTForSemanticSegmentation,
				    TFMobileViTModel,
				    TFMobileViTPreTrainedModel,
				)


else:
		import sys

		lowercase    :   Optional[int]						=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)